ترغب بنشر مسار تعليمي؟ اضغط هنا

Suppressing the non-Gaussian statistics of Renewable Power from Wind and Solar

190   0   0.0 ( 0 )
 نشر من قبل Peinke Joachim
 تاريخ النشر 2015
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

The power from wind and solar exhibits a nonlinear flickering variability, which typically occurs at time scales of a few seconds. We show that high-frequency monitoring of such renewable powers enables us to detect a transition, controlled by the field size, where the output power qualitatively changes its behaviour from a flickering type to a diffusive stochastic behaviour. We find that the intermittency and strong non-Gaussian behavior in cumulative power of the total field, even for a country-wide installation still survives for both renewable sources. To overcome the short time intermittency, we introduce a time-delayed feedback method for power output of wind farm and solar field that can change further the underlying stochastic process and suppress their strong non- gaussian fluctuations.



قيم البحث

اقرأ أيضاً

A fully renewable European power system comes with a variety of problems. Most of them are linked to the intermittent nature of renewable generation from the sources of wind and photovoltaics. A possible solution to balance European generation and co nsumption are European hydro power with its seasonal and North African Concentrated Solar Power with its daily storage characteristics. In this paper, we investigate the interplay of hydro and CSP imports in a highly renewable European power system. We use a large weather database and historical load data to model the interplay of renewable generation, consumption and imports for Europe. We introduce and compare different hydro usage strategies and show that hydro and CSP imports must serve different purposes to maximise benefits for the total system. CSP imports should be used to cover daily deficits, whereas hydro power can cover seasonal imbalances. If hydro is used in a Hydro First strategy, only around one quarter of North African Solar Power could be exported to Europe, whereas this number increases to around 60%, if a cooperative hydro strategy is used.
Analyzing football score data with statistical techniques, we investigate how the not purely random, but highly co-operative nature of the game is reflected in averaged properties such as the probability distributions of scored goals for the home and away teams. As it turns out, especially the tails of the distributions are not well described by the Poissonian or binomial model resulting from the assumption of uncorrelated random events. Instead, a good effective description of the data is provided by less basic distributions such as the negative binomial one or the probability densities of extreme value statistics. To understand this behavior from a microscopical point of view, however, no waiting time problem or extremal process need be invoked. Instead, modifying the Bernoulli random process underlying the Poissonian model to include a simple component of self-affirmation seems to describe the data surprisingly well and allows to understand the observed deviation from Gaussian statistics. The phenomenological distributions used before can be understood as special cases within this framework. We analyzed historical football score data from many leagues in Europe as well as from international tournaments, including data from all past tournaments of the ``FIFA World Cup series, and found the proposed models to be applicable rather universally. In particular, here we analyse the results of the German womens premier football league and consider the two separate German mens premier leagues in the East and West during the cold war times and the unified league after 1990 to see how scoring in football and the component of self-affirmation depend on cultural and political circumstances.
The Vietnamese Power system is expected to expand considerably in upcoming decades. However, pathways towards higher shares of renewables ought to be investigated. In this work, we investigate a highly renewable Vietnamese power system by jointly opt imising the expansion of renewable generation facilities and the transmission grid. We show that in the cost-optimal case, highest amounts of wind capacities are installed in southern Vietnam and solar photovoltaics (PV) in central Vietnam. In addition, we show that transmission has the potential to reduce levelised cost of electricity by approximately 10%.
The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources, fundamentally changing the configuration of energy management and introducing new criticalities that are only partly und erstood. In particular, renewable energies introduce fluctuations causing an increased request of conventional energy sources oriented to balance energy requests on short notices. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and the forecast of short time fluctuations related to renewable sources and to their effects on the electricity market. To account for the inter-dependencies among the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations on the power system and an agent based approach for the prediction of the market players behavior. Our model is a data-driven; it builds on one day ahead real market transactions to train agents behaviour and allows to infer the market share of different energy sources. We benchmark our approach on the Italian market finding a good accordance with real data.
Consensus about the universality of the power law feature in complex networks is experiencing profound challenges. To shine fresh light on this controversy, we propose a generic theoretical framework in order to examine the power law property. First, we study a class of birth-and-death networks that is ubiquitous in the real world, and calculate its degree distributions. Our results show that the tails of its degree distributions exhibits a distinct power law feature, providing robust theoretical support for the ubiquity of the power law feature. Second, we suggest that in the real world two important factors, network size and node disappearance probability, point to the existence of the power law feature in the observed networks. As network size reduces, or as the probability of node disappearance increases, then the power law feature becomes increasingly difficult to observe. Finally, we suggest that an effective way of detecting the power law property is to observe the asymptotic (limiting) behaviour of the degree distribution within its effective intervals.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا